As state-of-the-art products become an essential part of all aspects of today's high tech economy, the quality of such products becomes increasingly important. The control and reproducibility of quality continue to be the focus of efforts to meet the demand of the high tech economy. Process control is used to produce the most consistent product properties in a manufacturing process. Many production lines involve numerous processes to create a product. In production lines where intricate or otherwise information-sensitive manufacturing is performed, quality control is essential. Any number of factors may be significant and affect the quality of the product, and numerous problems may occur as a result of poor quality control.
Process control is very important in controlling the quality of the product. Improper process control can result in a product that is of little value or even useless to the user of the product. In such situations, the manufacturer can suffer (1) by paying the cost of manufacturing useless products, (2) by losing the opportunity to make a profit on an acceptable product, and (3) by lost revenue from a reduced selling price of poor products. Therefore, the success of the process control can even affect whether the manufacturer's business survives or fails.
Mathematical equations can be developed to assist in process control. These equations are developed using test data various forms of mathematical analysis. The equations provide an accurate guide of the manufacturing process. The equations can be used to determine the ranges of acceptable input values, or machine control settings, required to create final products with acceptable output parameter values. One problem with using mathematical equations to set the controls on manufacturing equipment is that the equations tend to shift over time due to environmental changes, degradation, part replacement, etc. In addition, these equations may not be accurate when applied to more than one manufacturing line because of variations between machines. Manufacturing machines typically vary in terms of machine settings. For example, the actual temperature of a machine may be different than the reading on the thermostat attached to the machine. These machine variations make the manufacturing process dependent on operators who are familiar with the specific machines. The operators will make adjustments during the machine set-up process to take into account machine variations and unique characteristics. For example, an operator may know, based on experience with the machine, that a particular manufacturing machine runs a few degrees hotter than the temperature shown on the thermostat. The operator will then set the thermostat a few degrees lower than the temperature specified by the temperature input variable. In this manner, the mathematical equations and therefore machine settings are interpreted and adjusted by operators who are familiar with the specific machines. This can result in mathematical models that are not accurate reflections of the actual manufacturing process.